aqwa-batch-execution-no-dedicated-python-package
Sub-skill of aqwa-batch-execution: No Dedicated Python Package.
Best use case
aqwa-batch-execution-no-dedicated-python-package is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Sub-skill of aqwa-batch-execution: No Dedicated Python Package.
Teams using aqwa-batch-execution-no-dedicated-python-package should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/no-dedicated-python-package/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How aqwa-batch-execution-no-dedicated-python-package Compares
| Feature / Agent | aqwa-batch-execution-no-dedicated-python-package | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Sub-skill of aqwa-batch-execution: No Dedicated Python Package.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# No Dedicated Python Package ## No Dedicated Python Package The PyAnsys metapackage (33+ packages) does **not** include a dedicated AQWA client as of 2025 R1. Automate AQWA via: - `subprocess` + direct `.DAT` / `Aqwa` executable (recommended for standalone) - `subprocess` + `runwb2` (for Workbench projects) - `.LIS` / `.AH1` text parsing for results extraction
Related Skills
digitalmodel-worktree-test-execution-with-shared-venv
Run digitalmodel tests from isolated worktrees without uv editable-dependency failures by using the main repo's existing virtualenv and PYTHONPATH.
plan-gated-issue-execution-wave
Execute a multi-issue architecture/planning wave in a plan-gated repo, then safely transition approved issues into implementation with file-based Codex prompts, local approval markers, subprocess monitoring, and cleanup handling for sandbox/hook edge cases.
work-around-merge-conflicts-in-test-execution
Run tests when repo has unresolved merge conflicts in config files by bypassing broken configs and executing tests directly
wave-based-parallel-plan-execution
Orchestrate phase execution by discovering dependencies, grouping into waves, spawning subagents, and collecting results with optional wave filtering
python-import-path-mismatch-debugging
Diagnose and fix ModuleNotFoundError when a package is installed but imports still fail due to environment/path mismatches
python-import-path-debugging
Diagnose ModuleNotFoundError when a package is installed but still fails to import
batch-syntax-repair-from-injection-errors
Detect and fix systematic syntax errors caused by line-injection scripts that split multiline constructs
batch-syntax-fix-with-regex-line-based-fallback
Fix repeated syntax errors across many files using regex, then fall back to line-based parsing when regex fails
batch-syntax-fix-regex-iteration
Iteratively fix widespread syntax errors across many files using regex refinement when initial patterns fail
batch-syntax-fix-pattern
Identify and repair cascading import/syntax errors across multiple files using regex-based line-scanning and verification
batch-regex-fix-import-syntax
Detect and fix mid-import blank-line syntax breaks across multiple files using line-based regex
plan-governance-vs-execution-boundary-for-adversarial-review
Keep stale-approval/governance remediation out of execution-path pseudocode, TDD, files-to-change, and deliverable acceptance when hardening a GitHub issue plan under adversarial review.